Face Shapes Of Diabetics And Non-Diabetics Described Using Geometric Morphometrics. Demayo, C, Torres, M, & Veña, C abstract bibtex Introduction: Analysis of the face is not only important for facial recognition, historical research, investigations, telecommunications or even games but also important in many health-related fields. Facial data is commonly obtained by direct anthropometric measurements but in this study we applied new tools in geometric morphometrics (GM) to describe morphological variations in the face of people with diabetes mellitus. Methods: Digital images of the faces of 54 non-diabetic and 63 diabetic patients were taken. For the males, images analyzed were those without moustache, beard, and eyeglasses and with neutral face expression were used in this study. A total of 63 manually positioned anthropomorphic landmarks were collected, the Cartesian coordinates of which were extracted using an image analysis and processing software. The faces were then aligned using Procrustes superimposition of the Cartesian coordinates to eliminate size differences and rotational translation. The size residuals left after the alignment were then used to reconstruct the face’ truss network using thin-plate spline grids. Variations in facial morphology were then explored using the methods of relative warps analysis and partial warps analysis supplemented with various multivariate statistical analyses. Results: While facial asymmetry seems to be a common feature among the individuals surveyed as shown by the first partial warp, relative warps revealed drooping of the brow ridge portion of the face, drooping of the chin and bulging of the cheek surface were observed among the diabetics. Ordination of the samples based on the shape residuals showed differences in face shapes between diabetics and non diabetics although no sexual dimorphism in face shapes was observed. The face shape of diabetics was found to be rounder and less tapered compared to that of non-diabetics. Common features among diabetics include facial asymmetry (elongation towards the right), drooping of the brow ridge, compression of the face towards the center, and downward folding of the skin in the area of the eyes. Conclusion: Geometric morphometrics is effective in describing face shapes between diabetics and non-diabetics and could be used in describing face shapes of other patients with specific health problems.
@article{demayo_face_nodate,
title = {Face {Shapes} {Of} {Diabetics} {And} {Non}-{Diabetics} {Described} {Using} {Geometric} {Morphometrics}},
abstract = {Introduction: Analysis of the face is not only important for facial recognition, historical research, investigations, telecommunications or even games but also important in many health-related fields. Facial data is commonly obtained by direct anthropometric measurements but in this study we applied new tools in geometric morphometrics (GM) to describe morphological variations in the face of people with diabetes mellitus. Methods: Digital images of the faces of 54 non-diabetic and 63 diabetic patients were taken. For the males, images analyzed were those without moustache, beard, and eyeglasses and with neutral face expression were used in this study. A total of 63 manually positioned anthropomorphic landmarks were collected, the Cartesian coordinates of which were extracted using an image analysis and processing software. The faces were then aligned using Procrustes superimposition of the Cartesian coordinates to eliminate size differences and rotational translation. The size residuals left after the alignment were then used to reconstruct the face’ truss network using thin-plate spline grids. Variations in facial morphology were then explored using the methods of relative warps analysis and partial warps analysis supplemented with various multivariate statistical analyses. Results: While facial asymmetry seems to be a common feature among the individuals surveyed as shown by the first partial warp, relative warps revealed drooping of the brow ridge portion of the face, drooping of the chin and bulging of the cheek surface were observed among the diabetics. Ordination of the samples based on the shape residuals showed differences in face shapes between diabetics and non diabetics although no sexual dimorphism in face shapes was observed. The face shape of diabetics was found to be rounder and less tapered compared to that of non-diabetics. Common features among diabetics include facial asymmetry (elongation towards the right), drooping of the brow ridge, compression of the face towards the center, and downward folding of the skin in the area of the eyes. Conclusion: Geometric morphometrics is effective in describing face shapes between diabetics and non-diabetics and could be used in describing face shapes of other patients with specific health problems.},
language = {en},
author = {Demayo, C and Torres, M and Veña, C},
pages = {6},
}
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A total of 63 manually positioned anthropomorphic landmarks were collected, the Cartesian coordinates of which were extracted using an image analysis and processing software. The faces were then aligned using Procrustes superimposition of the Cartesian coordinates to eliminate size differences and rotational translation. The size residuals left after the alignment were then used to reconstruct the face’ truss network using thin-plate spline grids. Variations in facial morphology were then explored using the methods of relative warps analysis and partial warps analysis supplemented with various multivariate statistical analyses. Results: While facial asymmetry seems to be a common feature among the individuals surveyed as shown by the first partial warp, relative warps revealed drooping of the brow ridge portion of the face, drooping of the chin and bulging of the cheek surface were observed among the diabetics. Ordination of the samples based on the shape residuals showed differences in face shapes between diabetics and non diabetics although no sexual dimorphism in face shapes was observed. The face shape of diabetics was found to be rounder and less tapered compared to that of non-diabetics. Common features among diabetics include facial asymmetry (elongation towards the right), drooping of the brow ridge, compression of the face towards the center, and downward folding of the skin in the area of the eyes. Conclusion: Geometric morphometrics is effective in describing face shapes between diabetics and non-diabetics and could be used in describing face shapes of other patients with specific health problems.","language":"en","author":[{"propositions":[],"lastnames":["Demayo"],"firstnames":["C"],"suffixes":[]},{"propositions":[],"lastnames":["Torres"],"firstnames":["M"],"suffixes":[]},{"propositions":[],"lastnames":["Veña"],"firstnames":["C"],"suffixes":[]}],"pages":"6","bibtex":"@article{demayo_face_nodate,\n\ttitle = {Face {Shapes} {Of} {Diabetics} {And} {Non}-{Diabetics} {Described} {Using} {Geometric} {Morphometrics}},\n\tabstract = {Introduction: Analysis of the face is not only important for facial recognition, historical research, investigations, telecommunications or even games but also important in many health-related fields. Facial data is commonly obtained by direct anthropometric measurements but in this study we applied new tools in geometric morphometrics (GM) to describe morphological variations in the face of people with diabetes mellitus. Methods: Digital images of the faces of 54 non-diabetic and 63 diabetic patients were taken. For the males, images analyzed were those without moustache, beard, and eyeglasses and with neutral face expression were used in this study. A total of 63 manually positioned anthropomorphic landmarks were collected, the Cartesian coordinates of which were extracted using an image analysis and processing software. The faces were then aligned using Procrustes superimposition of the Cartesian coordinates to eliminate size differences and rotational translation. The size residuals left after the alignment were then used to reconstruct the face’ truss network using thin-plate spline grids. Variations in facial morphology were then explored using the methods of relative warps analysis and partial warps analysis supplemented with various multivariate statistical analyses. Results: While facial asymmetry seems to be a common feature among the individuals surveyed as shown by the first partial warp, relative warps revealed drooping of the brow ridge portion of the face, drooping of the chin and bulging of the cheek surface were observed among the diabetics. Ordination of the samples based on the shape residuals showed differences in face shapes between diabetics and non diabetics although no sexual dimorphism in face shapes was observed. The face shape of diabetics was found to be rounder and less tapered compared to that of non-diabetics. Common features among diabetics include facial asymmetry (elongation towards the right), drooping of the brow ridge, compression of the face towards the center, and downward folding of the skin in the area of the eyes. 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